摘要
本研究提出一种基于稳态视觉诱发电位(steady state visual evoked potential,SSVEP)脑机接口的智能轮椅系统,该系统采用典型相关分析实时提取脑电信号,并产生控制信号,信号传输速率高、分析速度快。同时该轮椅采用了基于麦克纳姆轮的全方向移动系统,避免了传统轮椅转弯角度不好控制的问题。六位被试者参与了该系统的在线实验,实验结果证实,该系统可以在较高准确率的条件下,在平面内进行任意方向的移动。实验结果证实了该系统的可行性与有效性。
The intelligent wheelchair based on brain computer interface(BCI),currently,has some problems,such as the low accuracy of signal analysis and the difficulty of controlling the turning angle.In view of the problems,a wheelchair with steady state visual evoked potential(SSVEP)as control signal was proposed.The system used canonical correlation analysis to extract EEG signals in real time and generated control signals with high signal transmission rate and fast analysis speed.In addition,the using of Mecanum wheel made the proposed system achieve omni-direction moving without a turning.The corresponding experiment results demonstrate the wheelchair’s feasibility and effectiveness.
作者
高诺
翟文文
鲁加兴
吴林彦
鲁守银
GAO Nuo;ZHAI Wenwen;LU Jiaxing;WU Linyan;LU Shouyin(College of Information and Electrical Engineering,Shandong University of Architecture,Jinan 250101,China)
出处
《生物医学工程研究》
2018年第1期6-10,共5页
Journal Of Biomedical Engineering Research
基金
国家自然科学基金资助项目(61403237)
山东省科技重大专项资助项目(2015ZDXX0801A03)
山东省重点研发计划项目(2017CXGC1505)
关键词
稳态视觉诱发电位
脑机接口
智能轮椅
麦克纳姆轮
典型相关分析
Stable-state visual evoked potentials
Brain computer interface
Intelligent wheelchair
Mecanum wheel
Canonical correlation analysis
